Courses at University of Iowa or other places....

• 22C:031 Algorithms (Spring 2008)
  
  
• 22C:177 (22M178) Parallel and High Perf. Alg in Scientific Computing (Spring 2008)

• 22C:196:002: Topics in Computer Science: Advanced Scientific Programming (Fall 2006)

• 22C:031 Algorithms Spring 2006,    Spring 2007,
New Textbook used: Algorithms Design, Jon Kleinberg and Eva Tardos.


• 22C:019 Discrete Structures Fall 2005,   Spring 2007   
New Textbook used: Discrete Mathematical Structures: Theory and Applications, D.S. Malik and M.K. Sen.

• 22C:177:001 (22M178) High Performance and Parallel Computing (Fall 2005)
  

• 22C296 Topics in Computer Science: Numerical Computing (Comp. Science, U. of Iowa)  This course is about the design of numerical and scientific software. Topics include floating point arithmetic (round-off, underflow and overflow), algorithm stability, development of software, efficiency in time and memory, and tools for scientific programming.  Textbook: Numerical Computing with IEEE Floating Point Arithmetic, Michael L. Overton.   First time offered (Fall 2004).
  

• 22C296 Topics in Computer Science: Parallel Algorithms  (Comp. Science, U. of Iowa) We cover the design and implementation of diverse parallel algorithms. We implement programs for clusters using MPI. The application problems are from the broad area of scientific Computing. Textbook: Grama, Gupta, Karypis and Kumar, Introduction for Parallel Computing. First time offered (Fall 2003)
  

• 22C019 (former 34) Discrete Structures    (Comp. Science, U. of Iowa) Structures needed to design and understand algorithms and data structures.  Logic, quantifiers (``for all ...'' and ``there is a ...'') and mathematical induction, sets, sequences, relations, functions and algorithms, counting methods and recurrence relations, graph theory applied to Computer Science. Textbook: Jonshonbaugh, Discrete Mathematics.  Spring2003-Grades
  
  
• 22C:031 (former 44) Algorithms (Comp. Science ,U. of Iowa) Analysis of Algorithms Foundations, Sorting, searching,  Data Structures and Graph Algorithms. Prerequisite: 22C:17 (30), 22C:18 (20), 22C:19 (34). Textbook: Cormen, Leiserson and Rivest, Introduction to Algorithms. (chapters I, II, III and VI)  Fall2004-Grades
  

• 22C:231 (former 153) Design and Analysis of Algorithms (Comp. Science ,U. of Iowa)Analysis of Algorithms Foundations, Sorting, searching,  Data Structures and Graph Algorithms. Prerequisite: 22C:044. Textbook: Cormen, Leiserson and Rivest, Introduction to Algorithms. (chapters IV, V, VII) (Fall2002-Grades)      (Fall2000-Grades)
  

• 22C:177/22M:178 Parallel  and High Performance Algorithms in Scient. Comp. (Comp. Science and Math, U. of Iowa)   Design and Implementation of Computational Linear Algebra Algorithms for High Performance Computers. The background of students is diverse. Basic knowledge of one computer language and basic linear algebra is required. Prerequisite: any math or computer science numerical or linear algebra course. Textbook:  Peter S. Pacheco, Programming with MPI.


• 22M072/22C:055 Introduction to Numerical Analysis (Comp. Science and Math,  U. of Iowa).Prerequisite:22M: 22 or 22M:36 or 22M:46. Textbooks: Kendall Atkinson, Elementary Numerical Analysis and Van Loan, Introduction to Scientific Computing.
  
 
• CPSC 659 - Parallel/Distributed Numerical Algorithms and Applications. (Comp. Science, Texas A&M) A unified treatment of parallel and distributed numerical algorithms; parallel and distributed computation models, parallel computation of arithmetic expressions; fast algorithms for numerical linear algebra. Prerequisite: MATH 304, CPSC 653. Cross-listed with ELEN 659. Textbook: V. Kumar, A. Grama, A. Gupta and G. Karypis, Introduction to Parallel Computing.


• CPSC 653 - Computer Methods in Applied Sciences. (Comp. Science, Texas A&M)
Classical and modern techniques for the computational solution of problems of the type that traditionally arise in the natural sciences and engineering; introductions to number representation and errors, locating roots of equations, interpolation, numerical integration, linear algebraic systems, spline approximations, initial-value problems for ordinary differential equations, and finite-difference methods for partial differential equations. Prerequisite: CPSC 442 or MATH 417. Textbooks: D. Kincaid and W. Cheney, Numerical Analysis, and G. W Stewart, Afternotes on Numerical Analysis .
 
• 22C:021  Data structures. (CPSC210, Comp. Science, Texas A&M)
Methods for organizing data; design of algorithms for efficient implementation and manipulation of data structures. Prerequisite: CPSC 120. Textbook: T. L. Naps, Introduction to Data Structures and Algorithm Analysis.
 
• CPSC 660 - Computational linear algebra.(Comp. Science, Texas A&M)
Techniques in matrix computation: elimination methods, matrix decomposition, generalized inverses, orthogonalization and least-squares, eigenvalue problems and singular value decomposition, iterative methods and error analysis. Prerequisite: MATH 417 or equivalent or CPSC 442 or equivalent. Cross-listed with MATH 660. Textbooks: N. N. Trefethen and D. Bau III, Numerical Linear Algebra. Golub and Van Loan, Matrix Computations.
 
• Fortran (Computer Science Department, Metropolitan State College of Denver). Basic Introductory course for Computer Science students.  
  
  
• Calculus  (Mathematics Department, University of Colorado at Denver). Basic Calculus course for Business students.
  


• Trigonometry (Mathematics Department, University of Colorado at Denver). Undergraduate course for Mathematics students.